Introduction
Artificial Intelligence (AI) is the future of technology, and it is rapidly transforming various industries. The potential of AI is endless; therefore, many top artificial intelligence companies are gearing up to take this tech trend to a whole different level. Top artificial intelligence companies believe that AI is expected to contribute $15.7 trillion to the global economy by 2030. It is already changing the way we live and work. As the demand for AI increases, companies are investing heavily in this technology. In this blog, we will discuss the top 11 AI companies to watch out for.
Job Opportunities in Artificial Intelligence in 2023
Big Data Engineer
Average Base Salary: $96,661
Big Data Engineers working with top artificial intelligence companies build and manage big data systems for organizations. They work with tools like Spark and Hadoop and need to be proficient in programming languages like Python, R, and Java. A bachelor’s degree in computer science or mathematics is preferred, and those with a Ph.D. are given preference.
Business Intelligence Developer
Average Base Salary: $91,172
The artificial intelligence companies hire business intelligence developers to help assess complex data sets and identify trends. They work towards optimizing processes and workflows, improving business models, and enhancing efficiency. To become a Business Intelligence Developer, one needs a bachelor’s degree in computers, mathematics, or engineering, and proficiency in SQL servers, queries, and data warehouse design.
Data Scientist
Average Base Salary: $1,03,874
Data Scientists working with artificial intelligence companies to gather and analyze data that helps gain insights and make predictions. They need to be proficient in programming languages like Python, Scala, or SQL, and modern tools like Spark, Hadoop, Pig, or Hive. A master’s degree in mathematics or computer Science is preferred, and any advanced degree increases the chances of getting hired.
Machine Learning Engineer
Average Base Salary: $1,09,105
Artificial Intelligence companies hire machine learning engineers to build and maintain self-running software that facilitates machine learning. They work on image and speech recognition, fraud prevention, customer insights, and risk management. They need to have a strong command over predictive models and proficiency in programming, computing, and mathematics.
Don't miss out on your chance to work with the best
apply for top global job opportunities today!
Top 10 Artificial Intelligence Companies to watch out for in 2023
1. OpenAI
OpenAI is a research lab and an artificial intelligence company that focuses on developing advanced AI models and creating tools and platforms for building AI applications. The company’s mission is to develop safe AI that can benefit humanity. OpenAI has developed a range of AI models, including GPT-3, which is currently one of the most advanced natural language processing models.
OpenAI Artificial Intelligence products
- GPT-3: A natural language processing model that can generate human-like text, answer questions, translate languages, and perform various other language-related tasks.
- DALL-E: A neural network that can generate images from textual descriptions, creating original artwork that doesn’t exist in the real world.
- Codex: A machine learning model that can write code in various programming languages, based on natural language inputs.
- CLIP: A model that can understand and relate images and text, allowing it to perform tasks like visual question answering, image classification, and image search.
- RoboSumo: A reinforcement learning platform for training autonomous robots to play the game of sumo wrestling.
Job Opportunities with OpenAI
- Founding Data Scientist
- Software Engineer, ChatGPT
- Software Engineer (Full Stack) – DALL·E
- SDE – ML / AI Engineer
For more: Visit OpenAI
2. Google
Google is a multinational technology company that specializes in Internet-related services and products, including search engines, online advertising technologies, cloud computing, and software.
Google AI products
- Google Bard: A conversational artificial intelligence chatbot based on the LaMDA family of large language models, which was designed as a direct response to the rise of OpenAI’s ChatGPT.
- Google Assistant – An AI-powered virtual assistant that can answer questions, perform tasks, and interact with users through natural language commands.
- Google Translate – An AI-powered language translation service that can translate text, speech, images, and web pages between languages.
- Google Cloud AutoML – A suite of machine learning tools that enable businesses to build and deploy custom AI models without needing expertise in machine learning.
- Google Cloud AI Platform – A cloud-based platform that allows developers and data scientists to build, train, and deploy machine learning models at scale.
- Google Cloud Vision API – An AI-powered image recognition service that can identify objects, faces, and texts within images.
- Google Cloud Speech-to-Text – An AI-powered speech recognition service that can transcribe audio recordings into text.
- Google Cloud Natural Language API – An AI-powered natural language processing service that can analyze text to extract information about entities, sentiment, and syntax.
Job Opportunities with Google
- AI Consultant, Google Cloud
- Software Engineer, Machine Learning
- ASIC Design Engineer, Machine Learning
- System Performance Engineer, AI/ML
- Generative AI Specialist, Google Cloud
For More: Visit Google
3. DeepMind
DeepMind is a British Artificial Intelligence company acquired by Google in 2015. The company specializes in developing AI algorithms for gaming and simulation, healthcare, and natural language processing. DeepMind has developed AlphaGo, an AI program that beats a world champion at the game of Go, and AlphaFold, an AI system that can predict the 3D structure of proteins.
DeepMind AI products
- AlphaGo: A deep learning system that became the first computer program to defeat a human world champion in the ancient Chinese game of Go.
- AlphaZero: An algorithm that can master multiple games, including Go, chess, and shogi, without being explicitly programmed on how to play.
- WaveNet: A deep neural network for generating realistic-sounding speech, used in products like Google Assistant.
- DeepMind Health: A division of DeepMind that develops AI tools to help clinicians and researchers improve patient outcomes and advance medical research.
- MuZero: A reinforcement learning algorithm that can learn and plan in a wide range of games, without prior knowledge of the game rules.
Job Opportunities with DeepMind
- Machine Learning Engineer
- Robotics Engineer
- Research Scientist
- Deep Learning Engineer
For more: Visit DeepMind
4. NVIDIA
NVIDIA is a company that designs and produces high-performance graphics processing units (GPUs) used in training and deploying deep learning models. NVIDIA’s GPUs are widely used in the AI industry, and the company has developed a range of software tools to help developers build AI applications.
NVIDIA AI products
- NVIDIA Tesla: A series of GPU (graphics processing unit) accelerators designed for deep learning and other computationally intensive workloads.
- NVIDIA CUDA: A parallel computing platform and programming model that allows developers to harness the power of NVIDIA GPUs to accelerate applications.
- NVIDIA Deep Learning SDK: A collection of tools, libraries, and APIs for developing deep learning applications on NVIDIA GPUs.
- NVIDIA Jetson: A family of embedded AI computing platforms designed for autonomous machines like robots, drones, and smart cameras.
- NVIDIA DGX: A family of AI supercomputers built with NVIDIA GPUs and designed for deep learning training and inference workloads.
Job Opportunities with Nvidia
- Senior Data and Software Engineer, Generative AI Foundation Models
- Research Scientist, Deep Learning and Computer Vision
- Applied Scientist, Deep Learning
- AI Engineer, Generative AI Foundation Model Research – New College Grad
- Senior Applied Deep Learning Research Scientist
- Senior Applied Deep Learning Research Scientist, Computer Vision
For more: Visit NVidia
5. IBM
IBM is a multinational technology company that provides a range of AI products, including Watson, a question-answering AI system, and Cloud Pak for Data, an AI-powered data management and analysis platform. IBM has been investing in AI for decades and has developed a range of AI technologies that are used in various industries.
IBM AI products
- Watson: A suite of AI-powered tools and services that enable natural language processing, data analysis, and predictive modeling for businesses.
- IBM Cloud Pak for Data: A unified platform that combines data management, AI, and analytics tools to help organizations derive insights from their data.
- IBM PowerAI: An enterprise-grade deep learning platform that enables organizations to build and train deep learning models at scale.
- IBM AutoAI: An automated machine learning tool that enables users to build and deploy machine learning models without requiring extensive knowledge of data science.
- IBM Maximo: An AI-powered asset management platform that helps organizations optimize the performance and maintenance of their physical assets.
Job Opportunities with IBM
- Data Scientist
- Advisory Data Scientist
- Big Data Engineer
- Data Engineer: Data Warehouse
For more: Visit IBM
6. Microsoft
Microsoft is a technology company that offers AI services such as Azure Cognitive Services and Power Platform, which allow developers to build intelligent applications. Microsoft has also developed AI technologies for speech recognition, natural language processing, and computer vision.
Microsoft AI products
- Cortana: A personal assistant that uses natural language processing and machine learning to help users manage their daily tasks and access information.
- Microsoft Azure Cognitive Services: A collection of AI-powered APIs that enable developers to add intelligent features like speech recognition, language understanding, and image analysis to their applications.
- Microsoft Cognitive Toolkit: An open-source deep learning framework for building and training neural networks.
- Microsoft Dynamics 365 AI: A suite of AI-powered tools for customer service, sales, and marketing, designed to help businesses better engage with their customers.
- Microsoft Bot Framework: A platform for building, testing, and deploying intelligent bots that can interact with users through text, voice, and other channels.
Job Opportunities with Microsoft
- Principal Software Engineer
- Senior Machine Learning Engineer
- Senior Data Engineer
- Data Engineer
- Data Engineer II
For more: Visit Microsoft
7. Amazon
Amazon is a company that provides AI services through its cloud computing platform, Amazon Web Services (AWS). AWS offers a range of AI services, including Amazon SageMaker, which allows developers to build, train, and deploy machine learning models. Amazon has also developed AI-powered voice assistants, such as Alexa.
Amazon AI Products
- Alexa: Amazon’s voice-activated assistant that uses natural language processing and machine learning to respond to user requests and control smart home devices.
- Amazon Rekognition: An image and video analysis service that uses deep learning to detect objects, people, and activities in visual content.
- Amazon SageMaker: A fully managed machine learning platform that enables developers to build, train, and deploy machine learning models at scale.
- Amazon Lex: A service for building conversational interfaces using natural language understanding and automatic speech recognition.
- Amazon Personalize: A machine learning service that enables developers to build personalized recommendations for their applications based on user behavior and preferences.
Job Opportunities with Amazon
- Machine Learning Scientist
- Manager, Research Science
- Data Sciences Lead
- Sr SDE, Machine Learning (ML), Search
For more: Visit Amazon
8. Intel
Intel is a technology company that produces hardware optimized for AI workloads, including CPUs and specialized chips such as the Intel Neural Compute Stick. Intel has also developed software tools for AI, such as the Intel AI DevCloud, which allows developers to build and test AI applications in the cloud.
Intel AI products
- Intel Movidius Neural Compute Stick: A low-power AI accelerator that enables developers to run deep neural networks on edge devices like cameras and drones.
- Intel OpenVINO Toolkit: A development toolkit that enables developers to optimize their deep learning models for Intel hardware, including CPUs, GPUs, and FPGAs.
- Intel Nervana Neural Network Processors: A family of deep learning processors designed for high performance and scalability.
- Intel AI Builders Program: A program that provides resources and support to help AI developers and startups build, train, and deploy their models on Intel hardware.
- Intel Distribution for Python: A distribution of Python that includes optimized libraries for machine learning and data analytics, designed to take advantage of Intel hardware.
Job Opportunities with Intel
- Machine Learning Security Researcher
- Senior Deep Learning Software Engineering
- Deep Learning HW Engineer
For more: Visit Intel
9. Meta
Meta is a social media giant that uses artificial intelligence to improve user experience, including natural language processing and facial recognition technology. Meta has also developed AI-powered tools for content moderation and personalized recommendations.
- DeepFace: A facial recognition system that uses deep learning to identify faces in images.
- Prophet: A forecasting tool that uses time series analysis and machine learning to make predictions.
- PyTorch: An open-source machine learning framework that allows developers to build and train neural networks.
- Detectron2: A computer vision library that enables object detection, instance segmentation, and other visual recognition tasks.
- ParlAI: A framework for training and testing dialogue models using natural language processing and reinforcement learning.
Job Opportunities with Meta
- Data Scientist, Product – Generative AI
- Product Designer – Generative AI
- Software Engineer, Infrastructure – Generative AI
- Software Engineer, Machine Learning – Generative AI
- Software Engineer, Infrastructure – Generative AI
- Software Engineer, Product – Generative AI
- Data Engineer, Analytics – Generative AI
For more: Visit Meta
10. Tesla
Tesla is a company that produces electric cars and AI-powered autonomous driving technology. Tesla’s cars are equipped with a range of sensors and AI-powered algorithms that enable them to drive themselves.
Tesla AI products
- Autopilot: Tesla’s Autopilot system uses AI to help drivers stay safe on the road by providing semi-autonomous driving capabilities such as lane-keeping, adaptive cruise control, and self-parking.
- Full Self-Driving (FSD): Tesla’s FSD system aims to provide fully autonomous driving capabilities, allowing drivers to sit back and relax while the car takes them to their destination. It uses advanced AI algorithms to interpret data from the car’s sensors and make decisions on the road.
- Summon: This feature allows Tesla owners to remotely summon their cars to come to them using their phones. It uses AI to navigate the car to the owner’s location, avoiding obstacles along the way.
- Enhanced Summon: This feature is an extension of Summon that allows Tesla owners to remotely park their cars in tight spaces or navigate complex parking lots using their phones. It uses AI to interpret the car’s surroundings and make decisions on the best route to take.
- Tesla AI chip: Tesla has developed its own custom AI chip that powers its Autopilot and FSD systems. The chip is designed specifically for processing visual data from the car’s cameras and sensors, allowing it to make decisions on the road in real time.
- Tesla Vision: Tesla Vision is an AI-powered computer vision system that uses cameras to detect and interpret the world around the car. It is used to power features such as Autopilot, FSD, and Tesla’s Smart Summon technology.
- Neural Network: Tesla also uses neural networks, a type of machine learning technology, to improve its Autopilot and FSD systems. Neural networks allow the car to learn from past experiences and improve its driving performance over time.
Job Opportunities with Tesla
- Staff Software Engineer – Tesla Bot
- Machine Learning Engineer – Data Infrastructure, Autopilot AI
- Machine Learning Framework Engineer, Autopilot AI
- Firmware Engineer, Autonomy
- Machine Learning Engineer – Full Stack, Autopilot AI
- Quality Inspection Engineer – Vehicle Engineering
For more: Visit Tesla
Take control of your career and land your dream job
Sign up with us now and start applying for the best opportunities!
Conclusion
As AI is increasingly being used in industries such as healthcare, finance, and manufacturing, there is a growing demand for AI professionals who can help organizations leverage the technology to improve their processes and decision-making. In addition, the rise of automation and digital transformation is also creating opportunities for AI professionals who can help organizations optimize their workflows and improve their efficiency. Overall, the field of AI offers promising career prospects for AI Developers with the necessary skills and expertise. As AI technology continues to evolve and be adopted in new industries, the demand for AI professionals is likely to grow even further in the coming years. Sign up with Olibr now to learn more!
Frequently Asked Questions
Notable AI companies in India include TCS, Infosys, Wipro, HCL, Fractal Analytics, InMobi, and GreyOrange. Apart from these, MNCs such as Amazon, Google, Bosch, Intel, and Microsoft also offer great opportunities to work as AI professionals in India.
Artificial Intelligence in India has immense potential across various sectors. The National Strategy for Artificial Intelligence identifies core areas for AI application, including Healthcare, Agriculture, Education, Smart Cities, Infrastructure, and Transportation. As AI continues to evolve, it will play a transformative role in shaping India’s future.
Addressing bias in AI algorithms is a critical step towards building responsible and trustworthy AI technologies. A few steps that can be taken include diverse datasets, bias-aware algorithms, user feedback mechanisms, and fact-based processes.
AI can be applied across industries and sectors, including healthcare, finance, education, gaming, and language translation. testing process and guide the entire testing effort.
